This paper presents an evaluation of efficient radial basis function mesh deformation for complex iced geometries. Given the high computational cost of mesh deformation, state-of-the-art radial basis function techniques are used for data reduction. The principle procedures adopted are multi-level greedy surface point selection and volume point reduction. The multi-level greedy surface
Computational aerodynamic analyses of rotorcraft main rotor blades are performed in both hover and forward flight. The open-source SU2 code is used for rotor performance prediction. The core of the code is the set of RANS equations, which are solved for determining the flow. In hover, both steady-state and time-accurate modelling techniques of varying complexity are used and assessed. Simulation specific parameters which have a significant influence on the solution are also addressed. In forward flight, the code is developed to include the main rotor blade kinematics which is a prerequisite for modelling a trimmed rotor. Two databases are used for the validation of the rotor performance prediction. The renowned Caradonna-Tung experimental tests of a model rotor are used to evaluate the pressure distribution along the blade during hover. The extensive aerodynamic and aeroacoustic data survey of the AH-1G Cobra helicopter is used to assess the pressure distribution at different advancing and retreating azimuth angles during forward flight. The prediction capabilities of the solver in terms of rotor performance are demonstrated and are overall in good agreement with the measured data.
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